分离域中的模仿行为
Mimicking Behaviors in Separated Domains
摘要：
设计一种策略使一个系统模仿另一个系统的行为是计算机科学的许多领域中自然出现的问题。在这项工作中，我们解释这个问题的智能代理的背景下，从LTLf的角度来看，AI中常用的形式主义表达有限跟踪属性。我们的模型包括两个独立的动态域D_A和D_B，以及一个LTLf规范，该规范通过将D_A的行为（迹）上的属性映射到D_B的行为上的属性来形式化模仿的概念。目标是综合一个策略，逐步将D_A的每个行为映射到D_B的行为，以便满足规范。我们考虑几种形式的映射规范，从简单的到完整的LTLf，对于每一个，我们研究合成算法和计算性能。
英文摘要：
Devising a strategy to make a system mimicking behaviors from another system is a problem that naturally arises in many areas of Computer Science. In this work, we interpret this problem in the context of intelligent agents, from the perspective of LTLf, a formalism commonly used in AI for expressing finite-trace properties. Our model consists of two separated dynamic domains, D_A and D_B, and an LTLf specification that formalizes the notion of mimicking by mapping properties on behaviors (traces) of D_A into properties on behaviors of D_B. The goal is to synthesize a strategy that step-by-step maps every behavior of D_A into a behavior of D_B so that the specification is met. We consider several forms of mapping specifications, ranging from simple ones to full LTLf, and for each we study synthesis algorithms and computational properties.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
